Conventionally, a color copying machine, a color printing machine, and the like are known as a color image processing apparatus. The color image processing apparatus serves as an image input/output device that reads a color original image by read means, such as a color scanner, and outputs a copy of the original image by output means, such as a color printer.
However, if the image data are supplied intact from the read means to the output means, a copy image hardly renders the same colors as those of the original image.
Therefore, the colors of input image data must be corrected so that a copy image renders approximate colors to those of the original image. For example, methods of using a color correcting matrix or a color correcting neural network are adopted to correct the colors of the input image data. In these example methods, an output device outputs a full-color sample of the color gamut first, so that all the colors the output device can output will be corrected uniformly in the input image data. Then, the read means again reads the output color sample to construct color correcting means, such as a matrix and a neural network. The color image processing apparatus uses the color correcting means thus constructed. Accordingly, a copy image of the original image is produced by correcting the colors of the input image data using the above color correcting means.
Incidentally, the color correcting operation by the color correcting means takes longer as the color correcting accuracy is upgraded. In other words, the lower the color correcting accuracy, the faster the color correcting operation. For this reason, a conventional color image processing apparatus includes a plurality of color correcting means having their respective color correcting rates and color correcting accuracy, and the one with the highest color correcting rate is selected among those having allowable color correcting accuracy for the input image data.
However, the conventional color image processing apparatus always outputs a color-corrected image of the original image to judge the image quality thereof. In other words, all the input image data are subject to the color correcting operation each time the quality of a color-corrected image is judged. Thus, correcting the colors and judging the result has been time consuming, thereby making the overall operation inefficient.
Additionally, in the above color correcting methods, the color correcting matrix or neural network is constructed in advance as the color correcting means to correct the input image data in the entire color gamut of the output device. Although these methods are advantageous in that the image data are corrected in the entire color gamut of the output device with satisfactory accuracy, colors outside of that gamut are not corrected accurately and some colors can not be corrected as one desires.
Thus, the conventional color image processing apparatus has a problem that it can not produce a satisfactory copy image when an input image includes a number of colors which can not be corrected in a desired manner by the color correcting means.